A randomized multiple-baseline 1 - Blogs Konrad Lorenz...Verónica Cardona-Betancourt2 ([email protected]) 1Fundación Universitaria Konrad Lorenz 2Universitat Oberta de Catalunya

A randomized multiple-baseline 1

MANUSCRIPT PUBLISHED IN THE PSYCHOLOGICAL RECORD

Acceptance and commitment therapy focused on repetitive negative thinking for child

depression: A randomized multiple-baseline evaluation

Daniela M. Salazar1 ([email protected])

Francisco J. Ruiz1 ([email protected])

Eduar S. Ramírez1 ([email protected])

Verónica Cardona-Betancourt2 ([email protected])

1Fundación Universitaria Konrad Lorenz

2Universitat Oberta de Catalunya

Declarations of interest: none

Correspondence address: Francisco J. Ruiz, [email protected],

Fundación Universitaria Konrad Lorenz, Carrera 9 bis, Nº 62-43, Bogotá (Cundinamarca,

Colombia), Phone: (+57 1) 347 23 11 ext. 185

mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]


Abstract

The current study analyzes the efficacy of acceptance and commitment therapy (ACT)

focused on repetitive negative thinking (RNT) for child depression. A randomized,

nonconcurrent, multiple-baseline design was conducted with 9 children, aged between 8

and 13 years, who showed a main diagnosis of child depression. Measures of psychological

inflexibility, RNT, and generalized pliance were administered on a weekly basis throughout

the study, whereas measures of emotional symptoms and parents’ report of problematic

behavior were applied at pretreatment, posttreatment, and the 4-week follow-up. All

participants showed evidence of a treatment effect for psychological inflexibility and RNT.

The standardized mean difference effect sizes for single-case experimental designs were

very large for these measures. No participant showed the diagnosis of child depression or

comorbid disorders at the 4-week follow-up. Pretreatment to follow-up changes in

emotional symptoms and problematic behavior reported by parents were statistically

significant, with large effect sizes. RNT-focused ACT interventions for child depression

deserve further empirical tests.

Key words: Child depression; Acceptance and commitment therapy; Relational frame

theory; Repetitive negative thinking.


Acceptance and commitment therapy focused on repetitive negative thinking for child

depression: A randomized multiple-baseline evaluation

Recent estimations show that approximately 1 to 3% of children suffer from

depression (e.g., Costello, Erkanli, & Angold, 2006; Egger & Angold, 2006; Ford,

Goodman, & Meltzer, 2003), with few gender differences. These rates of depression

contrast significantly with those found in adolescents and adults, where females show

higher rates of depression, and the prevalence is about 5 to 10% in most studies (e.g.,

Avenevoli, Swendsen, He, Burstein, & Merikangas, 2015; Kessler & Bromet, 2013;

Kessler et al., 2003; Merikangas et al., 2010; Thapar, Collishaw, Pine, & Thapar, 2012). In

spite of its lower prevalence, child depression is an important concern because of its high

comorbidity with other emotional and behavioral disorders (Maughan, Collishaw, &

Stringaris, 2013) and its persistence. For instance, one-third of the children identified with

clinically significant levels of depressive symptoms remained symptomatic in a 2-year

longitudinal study (DuBois, Felner, Bartels, & Silverman, 1995). Additionally, child

depression has been associated with important negative consequences such as low

academic performance (DuBois et al., 1995), disrupted parent-child attachment (Brumariu

& Kerns, 2010), poor physical health (Fekkes, Pijpers, Fredriks, Vogels, & Verloove-

Vanhorick, 2006), unsatisfying social relationship (Perren & Alsaker, 2009), family

dysfunction (Sander & McCarty, 2005), higher risk of alcohol problems (Maughan et al.,

2013), and mortality by suicide (Rao, Weissman, Martin, & Hammond, 1993).

Psychological interventions for child depression have been considerably less

investigated than for adolescent and adult depression, with no child treatment achieving a

well-established empirical status (Weersing, Jeffreys, Do, Schwartz, & Bolano, 2017).

Regarding cognitive behavioral therapy (CBT) as a broad intervention, Weersing et al.


found that, among the seven high-quality studies identified in their review, only one study

showed positive findings favoring CBT versus waitlist or psychologically inert controls

(Kahn, Kehle, Jenson, & Clark, 1990). Accordingly, CBT only met the criteria for possibly

efficacious treatment for child depression. Less high-quality studies were found for

behavior therapy (BT), which also met the criteria for possibly efficacious treatment.

Considering broader eligibility study criteria, Zhou et al. (2015) found that

interpersonal therapy (IPT) and CBT had lower effects in treating child depression

compared to adolescent depression. Nevertheless, they concluded that IPT and CBT should

be considered as the best available approaches for child and adolescent depression. More

recently, Yang et al. (2017) identified nine studies analyzing the efficacy of CBT against

control conditions. At posttreatment, CBT was more effective than control conditions, but

the weighted effect size was small to medium (d = 0.41, 95% CI [0.18, 0.64]. Additionally,

subgroup analyses showed that CBT was more effective than nontreatment conditions but

equally effective than waitlist or psychological placebo.

In summary, the treatments for child depression tested so far have obtained mixed

evidence, with small to medium effect sizes. Accordingly, further research is needed to

establish the efficacy of CBT, BT, and IPT for child depression. Also, new psychological

interventions need to be developed and tested for child depression. Interestingly, few

studies have been conducted testing the efficacy of contextual cognitive-behavioral

therapies for child depression.

In recent years, there has been a growing interest in identifying transdiagnostic

processes involved in emotional disorders and developing psychological interventions

targeting them, such as acceptance and commitment therapy (ACT; Hayes, Strosahl, &

Wilson, 1999), metacognitive therapy (MCT; Wells, 2009), and rumination-focused


cognitive-behavioral therapy for depression (RF-CBT; Watkins, 2016). For instance, ACT

was initially developed for the treatment of experiential avoidance (Hayes & Wilson, 1994)

and has been redefined in broader terms for the treatment of psychological inflexibility

(Hayes & Strosahl, 2004). Regarding MCT and RF-CBT, they were developed focusing on

dismantling dysfunctional patterns of worry and rumination, which have been included

under the term repetitive negative thinking (RNT; Ehring & Watkins, 2008; Watkins,

2008). However, to our knowledge, none of these approaches have been analyzed in child

depression: ACT has been analyzed in the treatment of depression and anxiety disorders in

adolescents (Hayes, Boyd, & Sewell, 2011; Petts, Duenas, & Gaynor, 2017; Swain,

Hancock, Dixon, & Bowman, 2015), whereas MCT in the treatment of generalized anxiety

disorders in children (Esbjørn, Normann, Christiansen, & Reinholdt-Dunne, 2018).

In the last few years, brief ACT protocols have been developed and tested in adults,

which explicitly include the links among experiential avoidance, RNT, and psychological

inflexibility (Dereix-Calonge, Ruiz, Sierra, Peña-Vargas, & Ramírez, 2019; Ruiz, et al.,

2018; Ruiz, García-Beltrán, Monroy-Cifuentes, & Suárez-Falcón, in press; Ruiz, Luciano,

Flórez, & Suárez-Falcón, submitted; Ruiz, Riaño-Hernández, Suárez-Falcón, & Luciano,

2016). This approach has been termed RNT-focused ACT. Briefly, psychological

inflexibility entails the dominance of private experiences over chosen values and

contingencies in guiding action (Bond et al., 2011). One of the main processes involved in

psychological inflexibility is experiential avoidance, which is a pattern of verbal regulation

based on deliberate efforts to either avoid or escape from discomfiting private experiences

(Hayes, Wilson, Gifford, Follette, & Strosahl, 1996; Luciano & Hayes, 2001). Ruiz et al.

(2016) suggested that RNT in the form of worry and rumination is an especially

maladaptive experiential avoidance strategy because: (a) RNT tends to be the first reaction


to fear, the perception of not attaining personally relevant goals, and feelings of

incoherence; (b) RNT tends to prolong negative affect (e.g., Newman & Llera, 2011),

which usually leads to (c) engagement in additional experiential avoidance strategies in an

attempt to reduce prolonged discomfort (e.g., Caselli et al., 2013; Nolen-Hoeksema, Stice,

Wade, & Bohon, 2007; Wells, 2009); and (d) the repetition of this cycle generates an

inflexible and maladaptive repertoire.

The practical implication of this account is that ACT protocols primarily focused on

dismantling unconstructive RNT should produce quick changes and be particularly

effective for the treatment of emotional disorders. The study by Ruiz et al. (2016) showed

that a one-session, RNT-focused ACT protocol was sufficient to significantly reduce RNT,

with very large effect sizes, among adult participants suffering from mild to moderate

emotional disorders. Subsequent studies have shown that brief RNT-focused ACT protocol

(2- to 3-session protocols) obtained very large effect sizes in treating moderate and severe

emotional disorders, mainly depression and generalized anxiety disorders (Ruiz, et al.,

2018; Ruiz, García-Beltrán, et al., in press; Ruiz, Luciano, et al., submitted). Additionally,

Dereix-Calonge et al. (2019) showed that a web-based RNT-focused protocol was effective

in reducing emotional symptoms and improving valued living in clinical psychology

trainees compared to a waitlist control.

To our knowledge, RNT-focused ACT protocols have not been tested in children in

spite of the fact that RNT is a frequent phenomenon in children (Henker, Whalen, &

O’Neil, 1995; Păsărelu et al., 2016; Silverman, LaGreca, & Wasserstein, 1995).

Specifically, rumination has been closely associated with concurrent levels of depressive

symptoms in children (Abela, Vanderbilt, & Rochon, 2004) and predicts their increase over

time (Abela, Aydin, & Auerbach, 2007; Abela, Brozina, & Haigh, 2002). Accordingly, the


aim of this study was to evaluate the efficacy of a 3-session RNT-focused ACT protocol in

child depression. A nonconcurrent, randomized, multiple-baseline design was conducted

where the effect of the protocol was directly replicated in 9 participants with the main

diagnosis of child depression. The SCRIBE statement (Tate et al., 2016) was followed to

guide the reporting of this single-case experimental design.

Method

Participants

Nine children aged between 8 and 13 years participated in the study. Participants

were recruited through advertisements in social media beginning with the question: “Do

you think your child is irritable or sad?” The parents of 15 children showed interest in the

study and attended an assessment interview with their children. The inclusion criteria were:

(a) child between 8-13 years old, (b) presenting the main diagnosis of child depression

according to the Mini International Neuropsychiatric Interview for Kids and Adolescents

(MINI KID; Sheehan, Shytle, Milo, Janavs, & Lecrubier, 2009) diagnostic interview and

clinician’s judgment, and (c) showing a verbal intelligent quotient (IQ) higher than 70

according to the Kaufman Brief Intelligence Test (K-BIT, Kaufman & Kaufman, 1990).

The latter inclusion criterion was selected to guarantee that the child had a minimum verbal

repertoire to conduct the intervention. The exclusion criteria were: (a) current

psychological/psychiatric treatment, (b) having a psychological diagnosis prior to the study,

and (c) presenting a high risk of suicide according to the MINI KID. The second exclusion

criterion was adopted to avoid recruiting children with significant experience with

assessment and therapeutic contexts, which might act as an extraneous variable. None

participant was excluded for this reason.

The application of the inclusion and exclusion criteria led to the rejection of 6


potential participants: 1 individual was younger than 8 years and 5 did not meet the

depression criteria as the main diagnosis. The final sample consisted of 9 participants (4

girls; mean age = 10.22, SD = 2.11). Table 1 shows the demographic data of the

participants and diagnostic categories met. Six participants showed comorbid disorders

(oppositional defiant disorder in 4 participants, attention-deficit hyperactivity disorder in 3,

generalized anxiety disorder in 1, and separation anxiety in 1). Verbal IQ scores on the K-

BIT ranged from 76 to 126 (M = 100.78, SD = 18.16)

INSERT TABLE 1 ABOUT HERE

Design and Variables

A three-arm, nonconcurrent, randomized multiple-baseline design across

participants was implemented. Each cohort consisted of 3 participants. Participants in

Cohort 1 received the intervention after collecting 4 weeks of baseline, participants in

Cohort 2 after collecting 5 weeks of baseline, and participants in Cohort 3 after collecting 6

weeks of baseline. The randomization was conducted using the web-based tool Research

Randomized (Urbaniak & Plous, 2013). The implemented randomization procedure was

conducted because it significantly improves the internal validity of multiple baseline

designs (Kratochwill & Levin, 2010). The independent variable of the study was the

staggered introduction of a 3-session RNT-focused ACT protocol. Dependent variables

were measures of psychological inflexibility, RNT, generalized pliance, emotional

symptoms, diagnostic categories met according to the MINI KID, and

internalizing/externalizing symptoms according to the parent with closer contact with the

child. Measures of psychological inflexibility, RNT, and generalized pliance were applied

on a weekly basis, whereas the remaining measures were administered at pretreatment,

posttreatment, and 4-week follow-up to avoid participants’ burden.


Instruments

Avoidance and Fusion Questionnaire – Youth (AFQ-Y; Greco, Lambert, & Baer,

2008; Spanish version by Salazar et al., 2019). The AFQ-Y consists of 17 items, which are

rated on a 5-point Likert-type scale (4 = very true; 0 = not at all true) and measures

psychological inflexibility (e.g., “The bad things I think about myself must be true,” “I

push away thoughts and feelings that I don’t like”). The AFQ-Y was originally developed

and validated in USA (Greco et al., 2008). The original study found an alpha of .90 and a

one-factor structure. The AFQ-Y has shown a one-factor structure and excellent

psychometric properties (alpha of .89) in Colombia (Salazar et al., 2019). The mean score

of the AFQ-Y in a large Colombian nonclinical sample was 25.70 (SD = 15.19).

Perseverative Thinking Questionnaire (PTQ-C; Bijttebier, Raes, Vasey, Bastin,

& Ehring, 2015; Spanish version by Ruiz, Salazar, et al., in press). The PTQ-C consists of

15 items with a 5-point Likert-type scale (4 = almost always, 0 = never) that measure RNT

in children and adolescents (e.g., “The same thoughts keep going through my mind again

and again”). The PTQ-C showed excellent psychometric properties (alpha of .93) and a

one-factor structure in Colombia (Ruiz, Salazar, et al., in press). The mean score of the

PTQ-C in a large Colombian nonclinical sample was 23.16 (SD = 15.21).

Generalized Pliance Questionnaire – Children (GPQ-C; Salazar, Ruiz, Flórez, &

Suárez-Falcón, 2018). The GPQ-C consists of 8 items that are responded on a 5-point

Likert-type scale (5 = always true, 1 = never true). The questionnaire is the result of

reducing the original GPQ for adults (Ruiz, Suárez-Falcón, Barbero-Rubio, & Flórez, 2019)

by removing items with typical adult content and changing the wording of some items from

the original version to facilitate children’s understanding. The GPQ-C showed good

internal consistency (alpha of .81) in Colombian children and a one-factor structure


(Salazar et al., 2018). The mean score of the GPQ-C in a large Colombian nonclinical

sample was 20.30 (SD = 7.83).

Depression, Anxiety, and Stress Scale – Children (DASS-C; Szabó, submitted)

The DASS-C is an adaptation of the DASS-21 (Lovibond & Lovibond, 1995) for children.

It is a 24-item, 4-point Likert-type scale (3 = applies most of the time, 0 = does not apply)

consisting of sentences describing negative emotional states (e.g., “I felt tense and

uptight”). It contains three subscales (Depression, Anxiety, and Stress) and has shown good

internal consistency and convergent and discriminant validity. The method described in

Muñiz, Elosua, and Hambleton (2013) was used to translate the DASS-C into Spanish.

Alpha values in a previous study with a large Colombian nonclinical sample were

acceptable (.78, .79, and .69; Salazar et al., 2018), with a mean score for the overall scale of

19.40 (SD = 12.92), for Depression 5.18 (SD = 5.02), for Anxiety 5.82 (SD = 5.37), and for

Stress 8.91 (SD = 4.89).

Mental International Neuropsychiatric Interview for Kids and Adolescents

(MINI KID; Sheehan et al., 2009; Spanish adaptation by Colón-Soto, Díaz, Soto, &

Santana, 2005). The MINI KID is a brief diagnostic interview that explores the main

psychiatric disorders of Axis I of the DSM-IV-TR and the CIE-10. The administration of

the MINI KID takes approximately 15 minutes and consists of different modules identified

by letters belonging to a specific diagnostic category. The questions in each module have a

YES or NO answer. At the beginning of each module, there are filter questions that allow

advancing more quickly in the interview by ruling out the presence of specific disorders.

Child Behavior Checklist for Ages 6-18 years old (CBCL/6-18; Achenbach &

Rescorla, 2001) The CBCL is a questionnaire used to assess behavioral issues in children

ages 6-18 years old as reported by the parents. It consists of 113 items that are responded


on a 3-point Likert-type scale (2 = very true or often true, 0 = not true). The instrument has

shown excellent internal consistency and validity. The CBCL assesses a wide range of

behavior domains including anxiety/depression, withdrawal/depression, somatic concerns,

social problems, thought problems, attention problems, rule-breaking behavior, and

aggressive behavior. The CBCL provides an overall score, and internalizing, externalizing

and mixed problem scores.

Kaufman Brief Intelligence Test - 2 (KBIT-2; Kaufman & Kaufman, 1990). The

KBIT-2 is a brief (approximately 20 minutes) intelligence test for individuals from 4 to 90

years old. It was designed for traditional brief assessment purposes, such as screening,

conducting periodic cognitive reevaluations, and assessing cognitive functioning when it is

a secondary consideration. It assesses both verbal and nonverbal intelligence. Only the

verbal scale was administered, which has two types of items that evaluate crystallized

ability: verbal knowledge and riddles.

RNT-focused ACT Protocol

The protocol consisted of three, individual, 40-minute sessions. It was based on the

relational frame theory’s (RFT; Hayes, Barnes-Holmes, & Roche, 2001) definition of

psychological flexibility and the formation of the self (Luciano, 2017; Luciano, Valdivia-

Salas, & Ruiz, 2012; Ruiz & Perete, 2015; Törneke, Luciano, Barnes-Holmes, & Bond,

2016) and on previous similar protocols used in Ruiz et al. (2016, 2018). The aim of the

protocol was to develop the ability to discriminate ongoing triggers for worry/rumination,

take distance from them (i.e., defusion), and behave according to what is most important at

that moment for the individual in the long term (i.e., values).

Table 2 presents the content of the three protocol sessions (a complete description of

the protocol can be found at https://osf.io/xavhw/). The aims of Session 1 were: (a) to

https://osf.io/xavhw/


establish the differentiation between psychological inflexibility (PI) and psychological

flexibility (PF) reactions through multiple examples, (b) to practice the differentiation

between PI and PF, (c) to examine options for PI and PF in the child’s daily life, and (d) to

establish the child’s commitment to realize whether she was reacting in an inflexible or

flexible way toward her ongoing private experiences until the next session. The objectives

of Session 2 were: (a) to review the experience since the last session and advances in

discrimination of PI and PF, (b) to identify the counterproductive effects of RNT and

practice defusing from its triggers, and (c) to establish the commitment to continue

practicing the differentiation between PI and PF, and to try not to engage in

counterproductive RNT. Lastly, the aims of Session 3 were: (a) to review examples of

inflexible and flexible reactions since the last session, (b) to develop defusion skills through

multiple exemplar training, and (c) to identify valued actions and barriers and to establish

the committed actions for the next weeks.


Procedure

The study was conducted in the Clinical Psychology laboratory of a Colombian

university. The procedures of the study were approved by the Internal Ethics Committee.

The parents who showed interest in the research were invited to an assessment and

informative session with their children, led by the first and/or third authors. In this session,

the parents responded to the CBCL, and the K-BIT, MINI KID, AFQ-Y, PTQ-C, GPQ-C,

and DASS-C were administered to the children.

Parents’ of children who did not meet the inclusion criteria were given options for

inexpensive psychological treatment. If the children were eligible, the study functioning

was presented to the parents and the child, and both signed the informed consents. All


eligible individuals agreed to participate in the study. Afterward, participants and

experimenters agreed on how the children would respond to the AFQ-Y, PTQ-C, and GPQ-

C on a weekly basis. During the following weeks (4 to 6 weeks depending on the cohort

randomly assigned to the participant), participants provided the baseline data.

After collecting the baseline data, the protocol was implemented in an individual

format exclusively with the children. The ACT protocol was implemented by the first

author in all cases. She was a doctoral student who had received about 60 h of formal

training in ACT during the last two years (approximately 30 hours in the general ACT

model and 30 h of training in RNT-focused ACT protocols). The second author, who is an

experienced ACT researcher and has acted as a therapist in several clinical studies, trained

and supervised the therapist. Once the intervention had finished, the participants provided

data for posttreatment and follow-up on a weekly basis. Blinding procedures were not

implemented because the study only involved one intervention.

Data Analysis

In this section, we present the statistical analyses conducted to: (a) explore trends in

baseline for the AFQ-Y, PTQ-C, and GPQ-C, (b) the procedure followed to select the

statistical analyses after conducting a visual analysis, (c) the Bayesian approach followed to

analyze the evidence for a treatment effect, (d) the design-comparable standardized mean

difference computed, and (e) the Bayesian repeated-measures ANOVA to analyze the effect

of the intervention on the DASS-C and CBCL.

Analysis of trend in baseline. To assess the presence of significant trends in the

baseline, the Theil-Sen slope (Sen, 1968; Vannest, Parker, Davis, Soares, & Smith, 2012)

was computed before introducing the intervention. The Theil-Sen slope is a nonparametric

linear regression slope that does not assume any particular data distribution. It has stronger


power/precision than the Koenig and Tukey nonparametric slopes. The Theil-Sen slope

approximates the efficiency of linear regression when data meet all parametric assumptions

and it significantly exceeds efficiency when data are very nonnormal and skewed (Vannest

et al., 2012). Accordingly, although it is not very frequent in psychology studies, the Theil-

Sen slope is the method of choice in medicine and physical sciences for making decisions

with time-series data. The Theil-Sen slope was computed using the online calculator

provided by Vannest, Parker, and Gonen (2011).

Graphical analysis and selection of statistical analyses. Following a bottom-up

analysis of single-case experimental designs (SCED; Parker & Vannest, 2012), the results

were first graphed and, subsequently, statistical analyses for SCED were selected and

computed. In general, the data showed baselines with no significant trends. At the follow-

up, participants’ scores usually reached stability at the last three follow-up observations (2-

week to 4-week follow-ups). These observations are the most relevant ones in terms of the

clinical significance of the findings. Accordingly, we decided to focus the statistical

analysis of each participant on all baseline data and the last three follow-up points (see a

similar rationale in Au et al., 2017; Parker & Vannest, 2012; Ruiz et al., 2018). This

decision has the advantage of avoiding modeling linear improvement trends in the

treatment phase, which could lead to lines exceeding the range scale of the questionnaires

used.

Bayesian analysis of significant change for SCED. According to the previous

decision, we selected the Jeffreys-Zellner-Siow + Auto-Regressive Bayesian hypothesis

testing for single-subject designs (JZS+AR model; de Vries & Morey, 2013, 2015). The

JZS+AR Bayesian model is an adaptation of the JZS t-test (Rouder, Speckman, Sun,

Morey, & Iverson, 2009) that accounts for the serial dependence typical of single-subject


designs with an autoregressive (AR(1)) model. It provides a Bayes factor (Bar), which

quantifies the relative evidence in the data for the hypothesis of intervention effect (i.e., the

true means of both phases differ: Bar > 1) and for the hypothesis of no intervention effect

(i.e., the true mean in the baseline equals the true mean in the intervention phase: Bar < 1).

The Bayes factor can be also seen as the extent to which a rational person should adjust his

beliefs, expressed as relative odds, in favor of the hypothesis of intervention effect

according to the data (de Vries & Morey, 2013). Bayes factors were interpreted according

to the guidelines provided by Jeffreys (1961) and Wagenmakers, Wetzels, Borsboom, and

van der Maas (2011): 1 = No evidence of treatment effect; 1-3 = Anecdotal evidence of

treatment effect; 3-10 = Substantial or moderate evidence of treatment effect; 10-30 =

Strong evidence of treatment effect; 30-100 = Very strong evidence of treatment effect; and

>100 = Extreme evidence of treatment effect (note that Bar < 1 are interpreted in the same

way, but favoring the hypothesis of no treatment effect).

One of the distinctive features of Bayesian statistics is that they include prior

expectations of the parameters (e.g., the intervention effect). These prior expectations are

expressed by prior distributions that receive high density at plausible parameter values and

low density at implausible parameter values (Lee, 2004). Prior distributions can be

determined based on previous research, expert knowledge, scale boundaries, and statistical

considerations (de Vries & Morey, 2013).

To propose prior distributions, the JZS+AR model uses an estimation of two

relevant parameters: (a) an effect size of the intervention effect, termed δ, consisting of

standardizing the difference in true means between phases; and (b) a parameter for the lag 1

(р) autocorrelation, termed b. De Vries and Morey (2013) suggested three prior

distributions for δ in which it is located at 0 and follows a Cauchy distribution that differ in


width according to a factor termed r (suggested r values of 0.5, 1.0, and 2.0). This factor is

equal to half the inter-quartile range of the distribution (i.e., there is a 50% prior probability

that the effect size will be found within -0.5 and 0.5, -1.0 and 1.0, and -2.0 and 2.0,

respectively). The authors advocated using r = 1 by default because, in SCED, effect sizes

tend to be larger than in group studies (e.g., Beeson & Robey, 2006; Parker & Vannest,

2009). Additionally, the authors suggested three prior distributions for the lag 1

autocorrelation (b = 1, b = 5, b = 15) and advocated for the use of b = 5. This prior

distribution reflects the expectation of positive but low autocorrelations, while also

considering values of .4 or .5 plausible. This is consistent with the literature in SCED

showing that autocorrelation in this type of studies is reasonably low (e.g., Parker et al.,

2005).

Following the guidelines of de Vries and Morey (2013) and the results obtained in

similar studies (Ruiz, et al., 2016, 2018), we selected a value of r = 1 for the prior

distribution of δ. However, we also conducted a Bayesian sensitivity analysis that

investigated the robustness of the results with r values of 0.5 and 2.0, which posit higher

density in the Cauchy distribution at, respectively, medium and very large effect sizes.

Conducting sensitivity analyses is frequently suggested by Bayesian statisticians to

investigate whether the results obtained are excessively dependent on the selected prior

distribution (Gelman et al., 2014). Regarding the prior distribution of the autocorrelation,

we followed the suggestion provided by de Vries and Morey (2013) of choosing b = 5. All

analyses with the JZS+AR model were conducted in the BayesSingleSub R package (de

Vries & Morey, 2015). Due to prior evidence showing the effect of RNT-focused ACT

protocols (Ruiz et al., 2016, 2018), we conducted one-sided Bayes factor, testing the

hypothesis that δ = 0 against the alternative that δ > 0.


Design-comparable standardized mean difference. To obtain an overall estimate

of the effect size of the intervention, the design-comparable effect size for multiple-baseline

designs developed by Pustejovsky, Hedges, and Shadish (2014) was computed. This

standardized mean difference effect size for SCED shares the same metric as Cohen’s d,

typically used in group designs, which facilitates the direct comparison and integration

through meta-analysis of the results obtained in both types of designs. This d-statistic has a

formal mathematical development, requires at least three cases for computation, and

corrects for small sample bias using Hedges’ g. It is an extension of the standardized mean

difference advocated by Hedges, Pustejovsky, and Shadish (2012, 2013) that uses restricted

maximum likelihood estimation. It offers the possibility of obtaining the d-statistic by

controlling for baseline trend and taking into account change in slope. The R package

scdhlm was used to compute this d-statistic (Pustejovsky, 2016), following the guidelines

provided by Valentine, Tanner-Smith, and Pustejovsky (2016). According to the global

visual inspection of the dataset, we modeled baselines without trends including both fixed

and random effects for level. The treatment phase was modeled with linear trends with both

fixed and random effects at level and slope.

Bayesian repeated-measures ANOVA. To analyze the results on the DASS-C and

the CBCL, a Bayesian repeated-measures ANOVA was conducted with JASP 0.9.01 (JASP

Team, 2018). JASP provides a graphical interface of the R package BayesFactor, which

permits the computation of Bayes factors in standard designs (e.g., t-tests, ANOVA,

regression). The Bayesian ANOVA framework advocated by Rouder, Morey, Verhagen,

Swagman, and Wagenmakers (2017) suggests Cauchy prior distributions in which the

effect size of the factor, termed δ, is located at 0, and the researcher can modify the

parameter r between the recommended values of 0.2 to 1.0. This parameter represents the


width of the distribution (higher values of r places more density at higher effect sizes). The

authors advocated using r = 0.5 by default. However, we also conducted a Bayesian

sensitivity analysis that investigated the robustness of the results with r values of 0.2 and

0.8, which posit higher density in the Cauchy distribution at, respectively, small and large

effect sizes. Cohen’s d was computed with JASP for pretreatment to posttreatment

differences and for pretreatment to the 4-week follow-up.

Results

Within-participant results

The raw data of this study can be obtained at https://osf.io/7r3gn/. Figure 1 shows

the scores’ evolution on psychological inflexibility (AFQ-Y), RNT (PTQ-C), and

generalized pliance (GPQ-C). The Theil-Sen slope revealed that P9 showed a statistically

significant improving trend in the AFQ-Y, whereas P3 and P5 showed improving and

deteriorating trends for the GPQ-C, respectively. Accordingly, we decided not to compute

the JZS+AR analysis with these measures in these participants. The results of the Theil-Sen

slope can be seen at https://osf.io/a7z6q/. Visual inspection shows that the ACT protocol

was very effective in decreasing scores on psychological inflexibility and RNT in all

participants, whereas the change in generalized pliance was modest.

INSERT FIGURE 1 ABOUT HERE

Table 3 shows the effect sizes and Bar on the JZS+AR Bayesian model. All

participants showed at least strong evidence (i.e., Bar > 10) of intervention effect according

to Bayes factors in the AFQ-Y and PTQ-C. Specifically, all participants showed extreme

evidence in the PTQ-C, and 7 out of 8 in the AFQ-Y. Regarding the GPQ-C, only 4 out of

7 participants showed evidence of intervention effect (P1, P6, P8, and P9). Overall, the

Bayesian sensitivity analysis conducted with alternative prior distributions showed that the

https://osf.io/7r3gn/https://osf.io/a7z6q/


results were relatively robust (see the results of the sensitivity analysis at

https://osf.io/7bp3f/). In other words, the Bayes factors did not vary in a way that made the

interpretation of the results significantly different.


Table 1 shows that no participant showed the diagnosis of child depression

according to the MINI KID at posttreatment or at the 4-week follow-up. At posttreatment,

of the 6 participants who showed comorbid disorders, only P6 showed the diagnoses of

attention-deficit hyperactivity disorder (ADHD) and oppositional defiant disorder (ODD).

No comorbid disorders were identified at the 4-week follow-up.

Between-participant results

Results on weekly measures. Figure 2 shows the mean results across participants

in the AFQ-Y, PTQ-C, and GPQ-C. During the baseline, the mean scores on all measures

were one standard deviation higher than the mean scores in nonclinical Colombian children

(see Table 4). After introducing the intervention, the scores on all measures began to

decrease gradually. At posttreatment, the scores on the AFQ-Y and PTQ-C were about one

standard deviation below the mean scores in nonclinical participants. At the 4-week follow-

up, the scores on the AFQ-Y and PTQ-C stabilized at low levels, and the scores on the

GPQ-C decreased to approach the mean scores in nonclinical participants. Table 4 also

shows that the d-statistics for SCED were very large for the AFQ-Y (d = 3.74, 95% CI

[2.43, 5.43]) and PTQ-C (d = 3.14, 95% CI [1.88, 4.85]) and large for the GPQ-C (d = 1.14,

95% CI [0.01, 2.32]).


INSERT FIGURE 2 ABOUT HERE

https://osf.io/7bp3f/


Results on self-reported emotional symptoms. With regard to emotional

symptoms, Table 5 shows that participants obtained high scores on the DASS-Total and

each of its three subscales (approximately, scores one standard deviation higher than the

mean scores in nonclinical participants). The Bayesian repeated-measures ANOVA

revealed very strong evidence for the hypothesis of intervention effect for the DASS-Total

and the subscales (DASS-Total: BF = 53465.77; DASS-Depression: BF = 172.95; DASS-

Anxiety: BF = 67.42; DASS-Stress: BF = 4163000). The sensitivity analyses conducted

with alternative prior distributions showed that the results were robust (DASS-Total: BF =

22542.2 for r = .20, BF = 77990.9 for r = .80; DASS-Depression: BF = 82.34 for r = .20,

BF = 212.11 for r = .80; DASS-Anxiety: BF = 34.09 for r = .20, BF = 82.53 for r = .80;

DASS-Stress: BF = 1945000 for r = .20, BF = 6328000 for r = .80). The effect sizes were

very large both at the posttreatment and at the 4-week follow-up (DASS-Total: d = 2.57

and 2.12; DASS-Depression: d = 1.24 and 1.22; DASS-Anxiety: d = 1.57 and 1.18; DASS-

Stress: d = 2.61 and 3.11). After treatment, participants showed scores below the mean of

nonclinical participants in the total scores and each of the subscales.

Results on behavioral issues reported by the parents. Lastly, Table 5 also shows

the scores of the parent with closer contact with the child on the CBCL. Mean scores on the

CBCL were in the clinical range. The scores on all subscales decreased at the posttreatment

and at the 4-week follow-up. The Bayesian repeated-measures ANOVA revealed strong

evidence for the hypothesis of intervention effect for the CBCL-Total and the subscales

(CBCL-Total: BF = 21.50; CBCL-Internalizing: BF = 29.62; CBCL-Externalizing: BF =

10.04; CBCL-Mixed: BF = 22.22). The sensitivity analyses showed that the results were

also robust with regard to the CBCL (CBCL-Total: BF = 12.18 for r = .20, BF = 23.60 for r

= .80; CBCL-Internalizing: BF = 16.40 for r = .20, BF = 33.86 for r = .80; CBCL-


Externalizing: BF = 6.43 for r = .20, BF = 10.22 for r = .80; CBCL-Mixed: BF = 12.43 for

r = .20, BF = 24.49 for r = .80). The effect sizes were large both at the posttreatment and at

the 4-week follow-up (CBCL-Total: d = 0.91 and 1.21; CBCL-Internalizing: d = 1.07 and

1.35; CBCL-Externalizing: d = 0.71 and 1.06; CBCL-Mixed: d = 0.93 and 1.22).

Discussion

Recent research has shown that very brief RNT-focused ACT protocols can have

very large effect sizes in treating emotional disorders in adults (Ruiz et al., 2016, 2018, in

press). This study adapted the previous RNT-focused ACT protocols to the work with child

depression. A 3-session protocol was designed and its efficacy was analyzed with nine

children suffering from child depression as the main diagnosis (six participants showed

comorbid disorders). A three-arm, nonconcurrent, randomized multiple-baseline design

across participants was conducted. Self-reports of psychological inflexibility (i.e., AFQ-Y),

RNT (i.e., PTQ-C), and generalized pliance (i.e., GPQ-C) were administered on a weekly

basis, whereas measures of emotional symptoms (DASS-C) and parent-reported

problematic behavior (CBCL) were administered at pretreatment, posttreatment, and at the

4-week follow-up. Overall, participants showed scores one standard deviation higher than

the mean scores in nonclinical Colombian children and baselines did not show significant

improving or deteriorating tendencies.

All participants showed evidence of treatment effect in psychological inflexibility

and RNT, whereas 4 out of 7 participants did so in generalized pliance. The standardized

mean difference effect sizes for SCED were very large (AFQ-Y: d = 3.74; PTQ-C: d =

3.14; GPQ-C: d = 1.14). Importantly, these effect sizes are in the same metric as the

between-group Cohen’s d. At posttreatment, no participants showed the diagnosis of child

depression according to the MINI KID (P6 continued to show the diagnoses of ADHD and


ODD). At the 4-week follow-up, none of the participants suffered from child depression or

any other psychological disorder. Effect sizes were also very large for emotional disorders

as reported by the children (DASS-C Total: d = 2.12 at the 4-week follow-up) and

problematic behavior as reported by the parents (CBCL Total: d = 1.21 at the 4-week

follow-up).

Although the results of this study are very promising and encourage the

development of brief RNT-focused ACT protocols for children, some limitations are worth

noting. Firstly, as opposed to concurrent multiple baseline designs, the non-concurrent

multiple baseline design used in this study cannot control for history or maturation effects

that might occur simultaneously with the application of the intervention (Harvey, May, &

Kennedy, 2004). However, we think the weaknesses of nonconcurrent multiple baseline

designs are not especially significant in this case because: (a) only the results of participants

with no improvement trends in baseline are reported; (b) although there are only 4 to 6

measurement points of baseline, they represent weekly measures, which indicated that the

baseline showed no improvement trend across at least one month; (c) history confounding

effects seem to be less relevant when the intervention effect is replicated in 9 participants

with relatively similar results across them; and (d) the interventions were implemented at

different data points (after collecting 4, 5, or 6 baseline points), which reduces the

possibility that the time point in which the intervention was implemented would have had a

relevant effect. Additionally, the randomization of the participants to one of the three

cohorts significantly increases the internal validity of the experimental design (Kratochwill

& Levin, 2010). Secondly, a general limitation of usual multiple baseline designs is their

lack of active control conditions that control for the nonspecific effects of therapy. Thirdly,

the current study relied mostly on self-report measures, and the MINI KID was not applied


by a blind evaluator. Further studies might evaluate the intervention effect including

independent clinician-administered assessments and daily measures of the children’s

functioning. Fourthly, we did not administer the DASS-C on a weekly basis to avoid

participants’ burden. In this study, we were more interested in analyzing the changes in

process measures in more detail (i.e., psychological inflexibility, RNT, and generalized

pliance). Future studies should include more frequent assessments of emotional symptoms.

Lastly, only one therapist implemented the interventions, which reduces the external

validity of the study. Subsequent studies might employ several therapists trained in the

intervention.

The effect sizes obtained in this study are unusually large. For instance, the meta-

analysis conducted by Yang et al. (2017) found that CBT yields weighted effect sizes of d =

0.41 (95% CI [0.18, 0.64]) for child depression. This contrasts with the effect sizes

obtained in the current study in terms of emotional symptoms (d = 2.12 at the 4-week

follow-up in the DASS-Total). However, the experimental design of this study cannot

explain why the ACT protocol reached these unusually large effect sizes. Following Ruiz et

al. (2016), this could be due to two main reasons: (a) the protocol simultaneously addressed

the three strategies to promote psychological flexibility (Törneke et al., 2016) during the

sessions, and (b) the protocol was focused on disrupting the first and most pervasive

reaction to discomfiting thoughts and emotions (i.e., worry/rumination), which extends

discomfort and supports further EA strategies.

In conclusion, this study constitutes an initial and very promising step in the

analysis of brief RNT-focused ACT protocols for the treatment of child depression. Further

studies might conduct randomized controlled trials to compare the effect of the ACT


protocol with waitlist control conditions or brief versions of empirically established

treatments.

Compliance with Ethical Standards:

Conflict of Interest: The authors declare that they have no conflict of interest.

Ethical approval: All procedures performed in this study were in accordance with the

ethical standards of the institutional and/or national research committee and with the 1964

Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent: Informed consent was obtained from all individual participants included

in the study.


Availability of Data and Materials

The raw data of this study can be downloaded at https://osf.io/7r3gn/. The results of the

statistical analyses that are not reported in the manuscript for the sake of brevity can be

found at https://osf.io/a7z6q/ and https://osf.io/7bp3f/. The RNT-focused ACT protocol

employed in this study can be downloaded at https://osf.io/xavhw/

https://osf.io/7r3gn/https://osf.io/a7z6q/https://osf.io/7bp3f/https://osf.io/xavhw/


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Table 1

Demographical Data, K-BIT Scores, and Diagnoses at Baseline and the 4-Week Follow-Up

Sex Age Grade K-BIT

Verbal IQ

Diagnoses baseline Diagnoses

posttreatment

Diagnoses 4-week

follow-up

P1 F 10 5th 109 Depression, GAD None None

P2 M 8 3rd 110 Depression, separation

anxiety, ADHD

(combined)

None None

P3 M 9 3rd 101 Depression, ODD None None

P4 F 8 3rd 126 Depression, ADHD

(combined), ODD

None None

P5 M 13 5th 76 Depression None None P6 M 11 6th 91 Depression, ADHD

(attention), ODD

ADHD

(attention), ODD

None

P7 M 8 3rd 125 Depression, ODD None None

P8 F 13 7th 88 Depression None None P9 F 12 5th 81 Depression None None

Note. ADHD = Attention-Deficit Hyperactivity Disorder; GAD = Generalized Anxiety Disorder, K-BIT = Kaufman – Brief Intelligence Test, ODD = Oppositional Defiant Disorder.


Table 2

Summary of the ACT Protocol

Phase Aims Therapeutic interactions

Session 1 (40 min)

1. Differentiating between psychological inflexibility

(PI) and psychological

flexibility (PF) reactions.

2. Practicing the differentiation between experiential

avoidance (EA) and

repetitive negative thinking

(RNT) reactions (PI) and valued actions (VA).

3. Examining options for PI and PF in daily life.

4. Commitments for the next session

▪ Stating that we have thoughts and feelings all day and we have to choose between: (a) being the “wise king” by doing things that

make us to feel proud of ourselves because we want to be that

way, we are being responsible and growing as a person; (b) being

the “slave” of our thoughts and feelings because we move away from what is important for us.

▪ Introducing two examples of EA and RNT and two examples of VA, and situating them on a rug depicting the two options as

opposed directions.

▪ Asking the child to classify six new examples of EA and RNT (3) and VA (3).

▪ Examining how the child can be the “wise king” or the “slave” in 8 daily life situations. Emphasis on RNT as the beginning of

choosing to be the “slave.” ▪ Summarizing what things seem important for the child in view of

the previous responses.

▪ Asking the child to realize to what direction her actions go and to try to be the “wise king.”

Session 2

(40 min)

1. Review experience since the last session.

2. Identifying the counterproductive effect of

RNT and defusing from

triggers.

3. Commitment for the next

session.

▪ Exploration of actions as the “wise king” or the “slave” since the last session.

▪ Introducing RNT as being the “slave” of thoughts. ▪ Identify two typical situations in which the child engages in RNT. ▪ Go around exercise: while doing something symbolically

valuable, the therapist shows a trigger for RNT on a card and the

participant stops her actions and begins the RNT process going around a chair in circles. Every time the participant makes a loop,

she says the next thought of the chain and chooses to make

another loop (the same process is repeated 8 times). Then, the

participant is invited to engage again in the valued action and choose just to observe the triggers for RNT and go back to the

valued action. This exercise is done with the two situations

identified in the previous point.

▪ Balls as triggers exercise: The child is asked to walk toward a valued direction, but the therapist throws triggers for RNT in the

form of small balls. The child can choose between avoiding the

contact of the balls and not advancing or letting the balls contact

her and advancing toward the valued direction. ▪ Eye-contact exercise (Hayes et al., 1999): The participant and

therapist look into each other's eyes for 2 min while noticing

every thought and emotion and choosing to continue.

▪ Asking what the child was learnt in the session. ▪ Asking the child to realize in what direction her actions go and to

try not to engage in counterproductive RNT.

Session 3 (40 min)

1. Review experience since the last session.

▪ Exploration of actions as the “wise king” or the “slave” since the last session.


2. Developing defusion skills.

3. Identification of valued actions

▪ Multiple-exemplar training in defusion based on Luciano et al. (2011) and Ruiz and Perete (2015): hierarchically framing the

ongoing thoughts and feelings with the deictic “I” and providing

regulatory functions to that discrimination. ▪ Playing where’s Wally and free association exercise (based on

Wells, 2009): The child is asked to look for Wally and the

therapist says 8 words separated approximately by 10 s. The

participant has to notice what thought comes to her mind and

chooses between entangling with it and following the search for

Wally.

▪ Daydreaming and worrying exercise (based on Wells, 2009): The participant is invited to daydream for 2 minutes. Each 20 s, the therapist asks the participant to notice what she was thinking and

how she could choose between following or stopping the process.

The same process was repeated with a worry.

▪ Writing with the nondominant hand: The participant writes for 2 min with her nondominant hand while noticing the discomfort,

not entangling with it, and choosing to continue.

▪ The therapist asks the participant to list some valued actions that the she could do instead of being entangled with her thoughts

(“things that make her proud at the end of the day”), to identify

barriers, and establish commitment to practice the exercises in

order to choose to be the “wise king.”


Table 3

Results in the JZS+AR Analysis for each Participant and Measure with a Prior Distribution

with r = 1.

P1 P2 P3 P4 P5 P6 P7 P8 P9 %

AFQ-Y – Psychological

Inflexibility

δ 6.81 7.04 6.13 12.60 6.81 23.61 2.92 20.21 --

Bar >100 >100 >100 >100 >100 >100 24.4 >100 -- 100%

PTQ-C – Repetitive

Negative Thinking

δ 8.82 9.06 5.32 6.80 5.21 5.49 6.47 16.72 8.22

Bar >100 >100 >100 >100 >100 >100 >100 >100 >100 100%

GPQ-C –

Generalized Pliance

δ 1.90 0.29 -- 1.02 -- 1.46 -0.77 2.42 3.36

Bar 9.09 0.71 -- 2.19 -- 3.76 0.29 15.4 23.8 57.1%

Note. Bar = Bayes Factors of the JZS+AR model. Bar > 1 supports the hypothesis of intervention effect. Bar > 3

are in bold to highlight where at least substantial evidence of treatment effect was found.


Table 4

Means and Standard Deviations in each Self-Report Measure at Baseline, Posttreatment,

and 4-Week Follow-Up

Baseline Post 4-week

F-U

d-statistic for SCED

M

(SD)

M

(SD)

M

(SD)

d

(SE)

95% CI

AFQ-Y –

Psychological Inflexibility

43.87

(8.16)

12.22

(9.12)

7.33

(6.14)

3.74

(0.80)

[2.43, 5.43]

PTQ-C – Repetitive

Negative Thinking

40.16

(9.71)

7.67

(7.47)

7.00

(5.32)

3.14

(0.80)

[1.88, 4.85]

GPQ-C – Generalized

Pliance

29.29

(2.78)

26.11

(4.89)

22.44

(7.67)

1.14

(0.60)

[0.01, 2.32]

Note. AFQ-Y = Avoidance and Fusion Questionnaire - Youth; GPQ-C = Generalized Pliance Questionnaire –

Children; PTQ-C = Perseverative Thinking Questionnaire - Children.


Table 5

Means, Standard Deviations, Bayes Factors and 95% Confidence Intervals in the Scores of

the DASS-C and CBCL

Pre

M

(SD)

Post

M

(SD)

4-week

F-U M

(SD)

Pre vs. Post

d

95% CI

Pre vs. 4-

week F-U d

95% CI

DASS-C – Total 37.78

(14.39)

10.44

(12.69)

6.56

(7.23)

2.57

[1.16, 3.96]

2.12

[0.89, 3.32]

DASS-C – Depression 12.11

(8.91)

2.89

(3.95)

1.56

(2.88)

1.24

[0.33, 2.09]

1.22

[0.32, 2.08] DASS-C – Anxiety 8.44

(4.50)

3.00

(4.21)

2.67

(2.45)

1.57

[0.55, 2.55]

1.18

[0.30, 2.03]

DASS-C – Stress 17.22

(3.73)

4.56

(4.93)

2.33

(2.50)

2.61

[1.18, 4.01]

3.11

[1.47, 4.73] CBCL – Total

68.67

(46.39)

36.00

(29.63)

20.78

(19.18)

0.91

[0.11, 1.70]

1.21

[0.32, 2.07]

CBCL – Internalizing 17.00

(11.12)

8.78

(8.27)

5.56

(5.57)

1.07

[0.22, 1.89]

1.35

[0.41, 2.26] CBCL – Externalizing 20.22

(15.20)

11.00

(9.23)

5.44

(5.05)

0.71

[-0.05, 1.43]

1.06

[0.21, 1.87]

CBCL – Mixed

31.44

(21.09)

16.22

(13.10)

9.78

(9.15)

0.93

[0.12, 1.70]

1.22

[0.32, 2.08]

Note. CBCL = Child Behavior Checklist; DASS-C = Depression Anxiety and Stress Scale – Children; F-U =

Follow-up


Figure 1. Scores on psychological inflexibility (AFQ-Y), repetitive negative thinking (PTQ-C), and generalized pliance (GPQ-C) for

each participant.


Figure 2. Mean scores’ evolution on psychological inflexibility, repetitive negative

thinking, and generalized pliance. Bars represent 95% credibility intervals

Documents

A randomized multiple-baseline 1 - Blogs Konrad Lorenz...Verónica Cardona-Betancourt2 ([email protected]) 1Fundación Universitaria Konrad Lorenz 2Universitat Oberta de Catalunya